Data from: Using an insect mushroom body circuit to encode route memory in complex natural environments

Ants, like many other animals, use visual memory to follow extended routes through complex environments, but it is unknown how their small brains implement this capability. The mushroom body neuropils have been identified as a crucial memory circuit in the insect brain, but their function has mostly been explored for simple olfactory association tasks. We show that a spiking neural model of this circuit originally developed to describe fruitfly (Drosophila melanogaster) olfactory association, can also account for the ability of desert ants (Cataglyphis velox) to rapidly learn visual routes through complex natural environments. We further demonstrate that abstracting the key computational principles of this circuit, which include one-shot learning of sparse codes, enables the theoretical storage capacity of the ant mushroom body to be estimated at hundreds of independent images.

与诸多其他动物相仿，蚂蚁借助视觉记忆在复杂环境中沿长距离路径行进，但目前仍不清楚其微小的大脑如何实现这一行为能力。蕈形体神经纤维网（mushroom body neuropils）已被确定为昆虫大脑中的关键记忆回路，但针对其功能的探索大多局限于简单的嗅觉关联任务。本研究表明，最初用于描述果蝇（Drosophila melanogaster）嗅觉关联行为的该回路脉冲神经网络模型，同样能够解释沙漠蚁（Cataglyphis velox）快速学习复杂自然环境中视觉路径的能力。我们进一步证实，提取该回路的核心计算原理（包括稀疏编码的单次学习），可将蚂蚁蕈形体的理论存储容量估算为数百幅独立图像。